Baidu Files Patent for AI System Translating Animal Sounds to Human Language

Baidu, a prominent Chinese technology company, has filed a patent for a system designed to translate animal sounds, including feline meows, into human language. The patent, published in May by China’s intellectual property authority, outlines a method that collects animal vocalizations, behavioral patterns, and physiological signals such as heart rate. This data is then analyzed by an AI system to recognize the animal’s emotional state and map it to human language, aiming to facilitate deeper emotional communication and understanding between animals and humans.

Baidu’s approach is part of a broader trend in AI-powered research into animal communication. Recent studies have made significant strides in mapping cat vocalizations with high accuracy, and apps like MeowTalk claim to translate feline meows in real-time. In May, entrepreneur Vlad Reznikov unveiled Feline Glossary Classification 2.3, a system that identifies 40 distinct cat call types with over 95% accuracy, though it has yet to undergo peer review.

The potential benefits of understanding feline communication extend beyond mere curiosity. It could deepen human-animal bonds, improve pet welfare, and provide insights into how domestication has shaped interspecies dialogue. However, experts caution that true "cat translation" remains unlikely, despite AI’s progress. Psychologist Kevin Coffey, who studies animal vocalizations, described the idea of directly translating animal languages as "kind of total nonsense."

Baidu’s proposed system stands out for its comprehensive approach, incorporating body movement, temperature, and heart-rate data to create a richer context. This method aims to go beyond decoding simple meows like "feed me" and gauge emotional nuances. The company acknowledges that most animal translation tools rely too narrowly on either vocal cues or facial expressions, limiting their accuracy. However, significant barriers remain, including the lengthy patent review process, the need to prove real-world accuracy across diverse animals and dialects, and ethical questions around data collection.